A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
ACM Transactions on Information Systems (TOIS)
Retrieval and feedback models for blog feed search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Bloggers as experts: feed distillation using expert retrieval models
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Key blog distillation: ranking aggregates
Proceedings of the 17th ACM conference on Information and knowledge management
Blog site search using resource selection
Proceedings of the 17th ACM conference on Information and knowledge management
Finding Key Bloggers, One Post At A Time
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Information Retrieval on the Blogosphere
Foundations and Trends in Information Retrieval
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This paper investigates blog distillation where the goal is to rank blogs according to their recurrent relevance to the topic of the query. One of the main features of blogs is their relation to time but this important feature is under-utilized in the current blog retrieval methods. We propose a probabilistic framework to measure the stability of blogs relevance over time. We then study the effect of the proposed stability measure in the blog retrieval performance. We evaluate the proposed framework on the standard TREC Blog08 collection. The results show statistically significant improvements over state of the art models.